USG :: Ultrasonography

Value of S-Detect combined with multimodal ultrasound in differentiating malignant from benign breast masses

Na Li, Wanling Liu, Yunyun Zhan, Yu Bi, Xiabi Wu, Mei Peng

Egyptian Journal of Radiology and Nuclear Medicine.2024;[Epub] CrossRef

Biopsy or Follow-up: AI Improves the Clinical Strategy of US BI-RADS 4A Breast Nodules Using a Convolutional Neural Network

Mei Yi, Yue Lin, Zehui Lin, Ziting Xu, Lian Li, Ruobing Huang, Weijun Huang, Nannan Wang, Yanling Zuo, Nuo Li, Dong Ni, Yanyan Zhang, Yingjia Li

Exploring the Potential of Artificial Intelligence in Breast Ultrasound

Giovanni Irmici, Maurizio Cè, Gianmarco Della Pepa, Elisa D'Ascoli, Claudia De Berardinis, Emilia Giambersio, Lidia Rabiolo, Ludovica La Rocca, Serena Carriero, Catherine Depretto, Gianfranco Scaperrotta, Michaela Cellina

Critical Reviews™ in Oncogenesis.2024; 29(2): 15. CrossRef

Combined diagnosis of multiparametric MRI-based deep learning models facilitates differentiating triple-negative breast cancer from fibroadenoma magnetic resonance BI-RADS 4 lesions

Hao-lin Yin, Yu Jiang, Zihan Xu, Hui-hui Jia, Guang-wu Lin

Journal of Cancer Research and Clinical Oncology.2023; 149(6): 2575. CrossRef

AI: Can It Make a Difference to the Predictive Value of Ultrasound Breast Biopsy?

Jean L. Browne, Maria Ángela Pascual, Jorge Perez, Sulimar Salazar, Beatriz Valero, Ignacio Rodriguez, Darío Cassina, Juan Luis Alcázar, Stefano Guerriero, Betlem Graupera

The feasibility of a novel computer-aided classification system for the characterisation and diagnosis of breast masses on ultrasound: a single-centre preliminary test study

Y. Gu, W. Xu, Y. Liu, X. An, J. Li, L. Cong, L. Zhu, X. He, H. Wang, Y. Jiang

Can New Ultrasound Imaging Techniques Improve Breast Lesion Characterization? Prospective Comparison between Ultrasound BI-RADS and Semi-Automatic Software “SmartBreast”, Strain Elastography, and Shear Wave Elastography

Olga Guiban, Antonello Rubini, Gianfranco Vallone, Corrado Caiazzo, Marco Di Serafino, Federica Pediconi, Laura Ballesio, Federica Trenta, Corrado De Vito, Arenta Shkelqimi, Ludovica Costanzo, Daniele Fresilli, Veronica Rizzo, Vito Cantisani, Massimo Verg

Deep Learning in Different Ultrasound Methods for Breast Cancer, from Diagnosis to Prognosis: Current Trends, Challenges, and an Analysis

Humayra Afrin, Nicholas B. Larson, Mostafa Fatemi, Azra Alizad

Artificial intelligence in breast cancer: application and future perspectives

Journal of Cancer Research and Clinical Oncology.2023; 149(17): 16179. CrossRef

State-of-the-Art of Breast Cancer Diagnosis in Medical Images via Convolutional Neural Networks (CNNs)

Journal of Healthcare Informatics Research.2023; 7(4): 387. CrossRef

Diagnostic performance of ultrasound with computer-aided diagnostic system in detecting breast cancer

Pengjie Song, Li Zhang, Longmei Bai, Qing Wang, Yanlei Wang

Artificial intelligence in breast imaging: potentials and challenges

Jia-wei Li, Dan-li Sheng, Jian-gang Chen, Chao You, Shuai Liu, Hui-xiong Xu, Cai Chang

Physics in Medicine & Biology.2023; 68(23): 23TR01. CrossRef

Application of Artificial Intelligence in Breast Imaging: Current Landscape and Prospects

Korean Journal of Family Practice.2023; 13(4): 196. CrossRef

Application of artificial intelligence in predicting malignancy risk in breast masses on ultrasound

Mariah Carneiro Wanderley, Cândida Maria Alves Soares, Marina Marcondes Moreira Morais, Rachel Malheiros Cruz, Isadora Ribeiro Monteiro Lima, Rubens Chojniak, Almir Galvão Vieira Bitencourt

A Characterization Approach for the Review of CAD Systems Designed for Breast Tumor Classification Using B-Mode Ultrasound Images

Archives of Computational Methods in Engineering.2022; 29(3): 1485. CrossRef

The Added Value of a Computer‐Aided Diagnosis System in Differential Diagnosis of Breast Lesions by Radiologists With Different Experience

Qi Wei, Shu‐E Zeng, Li‐Ping Wang, Yu‐Jing Yan, Ting Wang, Jian‐Wei Xu, Meng‐Yi Zhang, Wen‐Zhi Lv, Christoph F. Dietrich, Xin‐Wu Cui

Journal of Ultrasound in Medicine.2022; 41(6): 1355. CrossRef

Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis

Jia-wei Li, Yu-cheng Cao, Zhi-jin Zhao, Zhao-ting Shi, Xiao-qian Duan, Cai Chang, Jian-gang Chen

Evaluation of computer-aided diagnosis in breast ultrasonography: Improvement in diagnostic performance of inexperienced radiologists

Luca Nicosia, Francesca Addante, Anna Carla Bozzini, Antuono Latronico, Marta Montesano, Lorenza Meneghetti, Francesca Tettamanzi, Samuele Frassoni, Vincenzo Bagnardi, Rossella De Santis, Filippo Pesapane, Cristiana Iuliana Fodor, Mauro Giuseppe Mastropas

Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules

Shu-Yi Lyu, Yan Zhang, Mei-Wu Zhang, Bai-Song Zhang, Li-Bo Gao, Lang-Tao Bai, Jue Wang

World Journal of Clinical Cases.2022; 10(2): 518. CrossRef

The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study

Qi Wei, Yu-Jing Yan, Ge-Ge Wu, Xi-Rong Ye, Fan Jiang, Jie Liu, Gang Wang, Yi Wang, Juan Song, Zhi-Ping Pan, Jin-Hua Hu, Chao-Ying Jin, Xiang Wang, Christoph F. Dietrich, Xin-Wu Cui

The application of artificial intelligence in the sonography profession: Professional and educational considerations

Christopher Edwards, Crispen Chamunyonga, Benjamin Searle, Tristan Reddan

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer

Young Seon Kim, Seung Eun Lee, Jung Min Chang, Soo-Yeon Kim, Young Kyung Bae

Enhancing Performance of Breast Ultrasound in Opportunistic Screening Women by a Deep Learning-Based System: A Multicenter Prospective Study

Chenyang Zhao, Mengsu Xiao, Li Ma, Xinhua Ye, Jing Deng, Ligang Cui, Fajin Guo, Min Wu, Baoming Luo, Qin Chen, Wu Chen, Jun Guo, Qian Li, Qing Zhang, Jianchu Li, Yuxin Jiang, Qingli Zhu

Clinical Application of Computer-Aided Diagnosis for Breast Ultrasonography: Factors That Lead to Discordant Results in Radial and Antiradial Planes

Ying Zhu, Weiwei Zhan, Xiaohong Jia, Juan Liu, Jianqiao Zhou

Cancer Management and Research.2022; Volume 14: 751. CrossRef

Application of Artificial Intelligence Computer-Assisted Diagnosis Originally Developed for Thyroid Nodules to Breast Lesions on Ultrasound

Si Eun Lee, Eunjung Lee, Eun-Kyung Kim, Jung Hyun Yoon, Vivian Youngjean Park, Ji Hyun Youk, Jin Young Kwak

Journal of Digital Imaging.2022; 35(6): 1699. CrossRef

Automated BI-RADS classification of lesions using pyramid triple deep feature generator technique on breast ultrasound images

Ela Kaplan, Wai Yee Chan, Sengul Dogan, Prabal D. Barua, Haci Taner Bulut, Turker Tuncer, Mert Cizik, Ru-San Tan, U Rajendra Acharya

Medical Engineering & Physics.2022; 108: 103895. CrossRef

Artificial Intelligence in Breast Ultrasound: The Emerging Future of Modern Medicine

Diagnostic accuracy of S-Detect to breast cancer on ultrasonography: A meta-analysis (PRISMA)

Differing benefits of artificial intelligence-based computer-aided diagnosis for breast US according to workflow and experience level

Si Eun Lee, Kyunghwa Han, Ji Hyun Youk, Jee Eun Lee, Ji-Young Hwang, Miribi Rho, Jiyoung Yoon, Eun-Kyung Kim, Jung Hyun Yoon

An AI model of sonographer’s evaluation+ S-Detect + elastography + clinical information improves the preoperative identification of benign and malignant breast masses

Pengfei Sun, Ying Feng, Chen Chen, Andre Dekker, Linxue Qian, Zhixiang Wang, Jun Guo

Using S-Detect to Improve Breast Ultrasound: The Different Combined Strategies Based on Radiologist Experienc

Zhu,MD Ying, Jia,MD Xiaohong, Dong,MD Yijie, Liu,MD Juan, Chen,MD Yilai, Yuan,MD Congcong, Zhan,MD Weiwei, Zhou,MD Jianqiao

ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY.2022; 6(4): 180. CrossRef

Evaluating breast ultrasound S-detect image analysis for small focal breast lesions

Boyuan Xing, Xiangyi Chen, Yalin Wang, Shuang Li, Ying-Kui Liang, Dawei Wang

S-Detect characterization of focal solid breast lesions: a prospective analysis of inter-reader agreement for US BI-RADS descriptors

Tommaso Vincenzo Bartolotta, Alessia Angela Maria Orlando, Maria Laura Di Vittorio, Francesco Amato, Mariangela Dimarco, Domenica Matranga, Raffaele Ienzi

Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses

Soo -Yeon Kim, Yunhee Choi, Eun -Kyung Kim, Boo-Kyung Han, Jung Hyun Yoon, Ji Soo Choi, Jung Min Chang

Yu-Ting Shen, Liang Chen, Wen-Wen Yue, Hui-Xiong Xu

European Journal of Radiology.2021; 139: 109717. CrossRef

Differential diagnosis of breast cancer assisted by S-Detect artificial intelligence system

Qun Xia, Yangmei Cheng, Jinhua Hu, Juxia Huang, Yi Yu, Hongjuan Xie, Jun Wang

Mathematical Biosciences and Engineering.2021; 18(4): 3680. CrossRef

AI-enhanced breast imaging: Where are we and where are we heading?

Almir Bitencourt, Isaac Daimiel Naranjo, Roberto Lo Gullo, Carolina Rossi Saccarelli, Katja Pinker

European Journal of Radiology.2021; 142: 109882. CrossRef

Added value of deep learning-based computer-aided diagnosis and shear wave elastography to b-mode ultrasound for evaluation of breast masses detected by screening ultrasound

Min Young Kim, Soo-Yeon Kim, Yeon Soo Kim, Eun Sil Kim, Jung Min Chang

Accuracy of ultrasonic artificial intelligence in diagnosing benign and malignant breast diseases

Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Liang Yongping, Ping Zhou, Zhang Juan, Zhao Yongfeng, Wengang Liu, Yifan Shi

JMIR Medical Informatics.2020; 8(3): e16334. CrossRef

The use of artificial neural networks to control the concentration of a model drug released acoustically

Hesham G. Moussa, Ghaleb A. Husseini, Salma E. Ahmad, Nahid Awad

S-Detect characterization of focal breast lesions according to the US BI RADS lexicon: a pictorial essay

Tommaso Vincenzo Bartolotta, Alessia Angela Maria Orlando, Luigi Spatafora, Mariangela Dimarco, Cesare Gagliardo, Adele Taibbi

Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study

Liang Yongping, Zhang Juan, Ping Zhou, Zhao Yongfeng, Wengang Liu, Yifan Shi

JMIR Medical Informatics.2020; 8(5): e18251. CrossRef

Reducing the number of unnecessary biopsies of US-BI-RADS 4a lesions through a deep learning method for residents-in-training: a cross-sectional study

Chenyang Zhao, Mengsu Xiao, He Liu, Ming Wang, Hongyan Wang, Jing Zhang, Yuxin Jiang, Qingli Zhu

Diagnostic Value of Breast Lesions Between Deep Learning-Based Computer-Aided Diagnosis System and Experienced Radiologists: Comparison the Performance Between Symptomatic and Asymptomatic Patients

Mengsu Xiao, Chenyang Zhao, Jianchu Li, Jing Zhang, He Liu, Ming Wang, Yunshu Ouyang, Yixiu Zhang, Yuxin Jiang, Qingli Zhu

Application of ultrasound artificial intelligence in the differential diagnosis between benign and malignant breast lesions of BI-RADS 4A

Sihua Niu, Jianhua Huang, Jia Li, Xueling Liu, Dan Wang, Ruifang Zhang, Yingyan Wang, Huiming Shen, Min Qi, Yi Xiao, Mengyao Guan, Haiyan Liu, Diancheng Li, Feifei Liu, Xiuming Wang, Yu Xiong, Siqi Gao, Xue Wang, Jiaan Zhu

A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound

Hee Jeong Park, Sun Mi Kim, Bo La Yun, Mijung Jang, Bohyoung Kim, Ja Yoon Jang, Jong Yoon Lee, Soo Hyun Lee

Ge-Ge Wu, Li-Qiang Zhou, Jian-Wei Xu, Jia-Yu Wang, Qi Wei, You-Bin Deng, Xin-Wu Cui, Christoph F Dietrich

World Journal of Radiology.2019; 11(2): 19. CrossRef

Computer‐Aided Diagnosis of Solid Breast Lesions With Ultrasound: Factors Associated With False‐negative and False‐positive Results

Jia‐yi Wu, Zi‐zhuo Zhao, Wen‐yue Zhang, Ming Liang, Bing Ou, Hai‐yun Yang, Bao‐ming Luo

Journal of Ultrasound in Medicine.2019; 38(12): 3193. CrossRef

Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images

European Radiology Experimental.2019;[Epub] CrossRef

Reliability Studies of Different Readers Using Computer Aided Diagnosis System in Ultrasound for Determining Identical Lesions in a Breast Phantom

Nari Choi, Bong Joo Kang, Na Young Jung, Sung Hun Kim, Jung Min Lee, Ga Eun Park

Iranian Journal of Radiology.2019;[Epub] CrossRef

A computer-aided diagnosing system in the evaluation of thyroid nodules—experience in a specialized thyroid center

Shujun Xia, Jiejie Yao, Wei Zhou, Yijie Dong, Shangyan Xu, Jianqiao Zhou, Weiwei Zhan

World Journal of Surgical Oncology.2019;[Epub] CrossRef

A Comparative Study of the Diagnostic Performance of Evaluating Breast Masses for Breast Surgeons versus S-DetectTM(Samsung Medison Co., Ltd, Seoul, Korea)

Haram Kim, Eiyoung Kwon, Youngsam Park, Eunhye Choi, Mijin Kim, Cheolseung Kim

Journal of Surgical Ultrasound.2019; 6(2): 58. CrossRef

Application of Computer‐Aided Diagnosis on Breast Ultrasonography: Evaluation of Diagnostic Performances and Agreement of Radiologists According to Different Levels of Experience

Eun Cho, Eun‐Kyung Kim, Mi Kyung Song, Jung Hyun Yoon

Journal of Ultrasound in Medicine.2018; 37(1): 209. CrossRef

Focal breast lesion characterization according to the BI-RADS US lexicon: role of a computer-aided decision-making support

Tommaso Vincenzo Bartolotta, Alessia Orlando, Vito Cantisani, Domenica Matranga, Raffele Ienzi, Alessandra Cirino, Francesco Amato, Maria Laura Di Vittorio, Massimo Midiri, Roberto Lagalla

Automated classification of focal breast lesions according to S-detect: validation and role as a clinical and teaching tool

Mattia Di Segni, Valeria de Soccio, Vito Cantisani, Giacomo Bonito, Antonello Rubini, Gabriele Di Segni, Sveva Lamorte, Valentina Magri, Corrado De Vito, Giuseppe Migliara, Tommaso Vincenzo Bartolotta, Alessio Metere, Laura Giacomelli, Carlo de Felice, Fe

Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience

Ji-Hye Choi, Bong Joo Kang, Ji Eun Baek, Hyun Sil Lee, Sung Hun Kim

Breast Ultrasound Computer-Aided Diagnosis: Analysis of Types of Errors

Min Kyung Jeong, Bong Joo Kang, Eunjeong Kim, Sung Hun Kim

Journal of the Korean Society of Radiology.2018; 79(3): 114. CrossRef

Comparison of the Diagnostic Performance of Breast Ultrasound and CAD Using BI-RADS Descriptors and Quantitative Variables

Yumi Kim, Bong Joo Kang, Jung Min Lee, Sung Hun Kim

Iranian Journal of Radiology.2018;[Epub] CrossRef

Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis

Si Eun Lee, Ji Eun Moon, Yun Ho Rho, Eun-Kyung Kim, Jung Hyun Yoon